Papers by Monem Mohammed
Ibn Al-Haitham Journal For Pure And Applied Science, Apr 20, 2023
Time series analysis is the statistical approach used to analyze a series of data. Time series is... more Time series analysis is the statistical approach used to analyze a series of data. Time series is the most popular statistical method for forecasting, which is widely used in several statistical and economic applications. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. The wavelet transform method provides signal information in both the time domain and frequency domain. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Fibonacci coefficient polynomials, as well as a comparison between ARIMA and wavelet-ARIMA. The time series data for daily wind speed is used for this study. From the obtained results, the proposed wavelet-ARIMA is the most appropriate wavelet for wind speed. As compared to wavelets the proposed wavelet is the most appropriate wavelet for wind speed forecasting, it gives us less value of MAE and RMSE.
International Journal of Scientific & Technology Research, Nov 25, 2014
Cox regression model is one of the models can be used in analyzing survival data and we variables... more Cox regression model is one of the models can be used in analyzing survival data and we variables and their survival time, so the cox regression is semi parametric model that consist two parts, the first part is n parametric part (e ሺβሻ ሖ) where ሺβሻ ሖ is the vector of unknown parameters, (one of censoring was taken from hospital with left-censored distribution of survival time is unknown. Selecting cox regression model as the best model to analysis data by checking the a model once graphically by using Kaplan-Meier estimator by using (partial likelihood) method and test the model parameter by using (Wald) test which shown that only two parameters(treatment and anemi status) are effect on survival time.
International Journal of Scientific & Technology Research, Jun 25, 2016
The instability in the world (and OPEC) oil process results from many factors through a long time... more The instability in the world (and OPEC) oil process results from many factors through a long time. The problems can be summarized as that the oil exports don't constitute a large share of N.I. only, but it also makes up most of the saving of the oil states. The oil prices affect their market through the interaction of supply and demand forces of oil. The research hypothesis states that the movement of oil prices caused shocks, crises, and economic problems. These shocks happen due to changes in oil prices need to make a prediction within the framework of economic planning in a short run period in order to avoid shocks through using computer techniques by time series models.
journal of kirkuk University For Administrative and Economic Sciences, 2012
The main objective of this study is to application one of the important multiple linear regressio... more The main objective of this study is to application one of the important multiple linear regression models for each road which is chosen in the city of sulamania. So that make application to pair wise multiple comparison procedure duncan and least significant difference (LSD) to explain the most effectiveness (LSD). The most effective factors in four main roads in sulamania city, which choose randomly. The noise measurements at (9) periodic times: Morning peak traffic (6.30 - 9.30) hours. Divided in to four periodic times, afternoon peak traffic (1.30 - 3.30) hours. Divided in to three periodic times and Evening peak traffic (6- 8) hours divided in to two periodic times
Passer Journal of Basic and Applied Sciences
Electricity Power Consumption Forecasting (EPCF) plays an essential role in global electricity di... more Electricity Power Consumption Forecasting (EPCF) plays an essential role in global electricity distribution systems that has a significant impact on the operation, control, and planning for the production and distribution of electricity. Due to the complexity, and uncertainty of electricity consumption, especially when the amount of load consumed during different hours is not the same, performing forecasting by using the classical method is inaccurate. To strengthen the efficiency, the time series method that uses a fuzzy approach based on refined entropy is presented in the upcoming article. First, given the specified features, the minimization principle approach of entropy (MPAE) is pursued to define the longitude of each interval in the world of discourse. Secondly, a fuzzy relation matrix of time-invariant is constructed according to the first-order model of fuzzy time series, and the minimum fixed amount of time that the data approach the steady state is obtained using the entropy of the fuzzy set, respectively. Eventually, the forecast results are calculated based on the operation of the maximum combination and the principle of full membership. To show the whole forecasting process, hourly data from July 2022 to September 2022 in Sulaymaniyah / Iraq province is used. Results are compared to the traditional statistical (ARIMA) model, and it indicates that the mean squared error and other criteria of the forecasting error in the entropy based on the fuzzy method are significantly better than the traditional statistical model.
Discrete Dynamics in Nature and Society
Wind energy is one of the speedy processing technologies in the energy generation industry and th... more Wind energy is one of the speedy processing technologies in the energy generation industry and the most economical methods of electrical power generation. For the reliability of system, it is wanted to improve highly appropriate wind speed forecasting methods. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. This technique has proven useful in a nonstationary time series forecasting. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Lucas polynomials, as well as a comparison between an artificial neural network (ANN) and wavelet-artificial neural network (WNN). We used the proposed wavelet, Mexican hat, Morlet, Gaussian, Haar, Daubechies, and Coiflet to transform the wind speed data using the continuous wavelet transform (CWT). MATLAB software was used to implement the CWT and ANN. The proposed models were applied in the meteorological field to forec...
journal of kirkuk University For Administrative and Economic Sciences, 2012
The main objective of this study is to application one of the important multiple linear regressio... more The main objective of this study is to application one of the important multiple linear regression models for each road which is chosen in the city of sulamania. So that make application to pair wise multiple comparison procedure duncan and least significant difference (LSD) to explain the most effectiveness (LSD). The most effective factors in four main roads in sulamania city, which choose randomly. The noise measurements at (9) periodic times: Morning peak traffic (6.30 - 9.30) hours. Divided in to four periodic times, afternoon peak traffic (1.30 - 3.30) hours. Divided in to three periodic times and Evening peak traffic (6- 8) hours divided in to two periodic times
Global Health Action, 2020
Background: Monitoring Sustainable Development Goal indicators (SDGs) and their targets plays an ... more Background: Monitoring Sustainable Development Goal indicators (SDGs) and their targets plays an important role in understanding and advocating for improved health outcomes for all countries. We present the United Nations (UN) Inter-agency groups' efforts to support countries to report on SDG health indicators, project progress towards 2030 targets and build country accountability for action. Objective: We highlight common principles and practices of each Inter-agency group and the progress made towards SDG 3 targets using seven health indicators as examples. The indicators used provide examples of best practice for modelling estimates and projections using standard methods, transparent data collection and country consultations. Methods: Practices common to the UN agencies include multi-UN agency participation, expert groups to advise on estimation methods, transparent publication of methods and data inputs, use of UN-derived population estimates, country consultations, and a common reporting platform to present results. Our seven examples illustrate how estimates, using mostly Bayesian models, make use of country data to track progress towards SDG targets for 2030. Results: Progress has been made over the past decade. However, none of the seven indicators are on track to achieve their respective SDG targets by 2030. Accelerated efforts are needed, especially in low-and middle-income countries, to reduce the burden of maternal, child, communicable and noncommunicable disease mortality, and to provide access to modern methods of family planning to all women. Conclusion: Our analysis shows the benefit of UN interagency monitoring which prioritizes transparent country data sources, UN population estimates and life tables, and rigorous but replicable modelling methods. Countries are supported to build capacity for data collection, analysis and reporting. Through these monitoring efforts we support countries to tackle even the most intransient health issues, including the pandemic caused by SARS-CoV-2 that is reversing the hard-earned gains of all countries.
The instability in the world (and OPEC) oil process results from many factors through a long time... more The instability in the world (and OPEC) oil process results from many factors through a long time. The problems can be summarized as that the oil exports don’t constitute a large share of N.I. only, but it also makes up most of the saving of the oil states. The oil prices affect their market through the interaction of supply and demand forces of oil. The research hypothesis states that the movement of oil prices caused shocks, crises, and economic problems. These shocks happen due to changes in oil prices need to make a prediction within the framework of economic planning in a short run period in order to avoid shocks through using computer techniques by time series models.
IJSTR, 2016
The instability in the world (and OPEC) oil process results from many factors through a long time... more The instability in the world (and OPEC) oil process results from many factors through a long time. The problems can be summarized as that the oil exports don't constitute a large share of N.I. only, but it also makes up most of the saving of the oil states. The oil prices affect their market through the interaction of supply and demand forces of oil. The research hypothesis states that the movement of oil prices caused shocks, crises, and economic problems. These shocks happen due to changes in oil prices need to make a prediction within the framework of economic planning in a short run period in order to avoid shocks through using computer techniques by time series models.
Comparison between SARIMA and SARIMAX time series by Monem Mohammed
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Papers by Monem Mohammed
Comparison between SARIMA and SARIMAX time series by Monem Mohammed